Advanced and dangerous cyber threats have grown rapidly, and thus has led to the need to convert the traditional rule-based cybersecurity connection to Artificial Intelligence (AI)-mediated Cyber Threat Intelligence (CTI) systems. Although the role of AI in improving the cyber resilience of organizations has been identified to hold a potential, the empirical knowledge of the drivers behind its adoption in the emerging technology hubs is not yet unified. This paper is an empirical exploration into CTI adoption determinants of using AI in IT and cybersecurity firms based in Bengaluru, India, only. Based on the Technology-Organization-Drunken Environment (TOE) model and Protection Motivation Theory (PMT), a research model was constructed based on five central variables that include: Perceived AI Efficacy (PAIE), Organizational AI Readiness (OAIR), Cyber Threat Susceptibility (CTS), Top Management Support (TMS), and Regulatory Compliance Pressure (RCP) in relation to the Digital Personal Data Protection Act (DPDPA) 2023. The results of the analysis of the 124 IT and security managers of Bengaluru were determined using the Partial Least Squares Structural Equation Modeling (PLS-SEM). As the results show, the greatest predictors of the behavioral intention to embrace AI-CTI systems are Top Management Support and Regulatory Compliance Pressure. Moreover, AI Readiness in the organization plays a big role in mediating the relationship between the Perceived AI Efficacy and adoption intention. The paper gives 15 analytical tables and SEM pathways diagrams in details, which represents a strong empirical evidence and managerial implications to escape the AI cybersecurity paradox, labor organization changes, and excessive data protection requirements in the year 2026.